Typically, noise cancellation systems enhance the quality of speech in an environment having a relatively high level of ambient background noise (a noisy environment). A number of systems attempt to estimate background noise so that it can be subtracted from a signal.
Acoustic noise suppression has been implemented in a wide variety of settings such as basic hearing aids (see, e.g., Langberg); cooling fans, e.g., those found in computers (see Hill); driving devices in a chamber, for instance, a compressor (see Nagayasu); propeller driven aircraft (see Elliot); vehicle seats (see Ziegler '600); and voice transmission in an emergency vehicle (see Cantrell). Dual-input adaptive cancelers are known in the communications areas (see, e.g., Widrow. 1975). Widrow (1975) particularly illustrates the use of least mean square (LMS) gradient control algorithms in such apparatus (see also Zinser and Zeiqler). These publications are cited at the end of this specification.
Although these publications describe numerous acoustic noise suppression techniques, they fail to provide an acoustic noise suppression technique as set forth in the present invention. For example, in Borth, a noise estimation means generates and stores an estimate of background noise based upon a pre-processed input signal; a noise detection means performs speech/noise decision based upon a post-processed signal; and the noise detection means provides the speech/noise decision to noise estimation means so that the background noise estimate is updated only when the detected minima of post-processed signal energy is below a predetermined minima. A key difference between the present invention and Borth is that the present invention employs an improved speech detection means utilizing delays so as to minimize any possibility of lost unvoiced consonants, preferably by use of an adaptive non-parametric detector statistic based upon a Kolmogorov-Smirnov Test, to more evenly discriminate speech from a given user from background noise consisting of several voices.
Langberg relates to an electronic earplug seated in the concha fossa (the hollow external portion adjacent to the opening of the ear canal), which acts as a passive acoustical barrier. The earplug contains a summing microphone which detects noise which has penetrated the occluded ear canal and the output signal from the summing microphone is used to initiate active noise reduction. Langberg does not appear to teach or suggest an in-ear or in-earpiece microphone for detecting speech, nor does Langberg describe or the headset of the present invention.
More specifically, Langberg does not appear to teach or suggest compensation for use in the ear. Langberg also does not appear to teach or suggest filtering to account for density changes in the ear which may otherwise lead to ear canal/middle ear impedance mismatching or instabilities at certain frequencies.
Further, an embodiment of the present invention utilizes an "in-ear" microphone to transmit speech when a push-to-talk or voice-operated-switch (VOX) switch is depressed or activated. The embodiments of the present invention also utilize a "reference sensor" located in an external portion of the "earplug", which is acoustically isolated from the earplug, to measure background noise. Another embodiment of the present invention employs an adaptive filter means, e.g., using a least mean square (LMS) algorithm, to account for variations in the feedback path. These features do not appear to be taught or suggested by Langberg.
Zeigler '188 relates to canceling only harmonic disturbances. Unlike Zeigler, in the present invention, any type of random or harmonic disturbances may be canceled. Further, in the present invention, there are compensators for feedback and reference paths to ensure that the channels are matched in both amplitude and phase over a specified band; this is done non-adaptively. Furthermore, the present invention also provides filtering compensation to achieve broadband as well as narrow band cancellation.
Nagayasu merely eliminates noise without any apparent teaching or suggestion to enhance speech. Landgarten merely relates to monitoring, testing and controlling vibration. Sasaki does not appear to teach or suggest employing an adaptive system that automatically compensates for changes in feedback as in the present invention. For instance, the present invention may use filtering to compensate for the speaker/ear canal transfer function (to match reference and feedback channels). This filtering does not non-adaptively couple the reference and feedback signals. In the present invention, filtering is used to minimize signal decorrelation effects so as to extend the ability of the adaptive processor to cancel noise when the noise statistics and feedback path change.
Stettiner is akin to Borth and likewise fails to teach or suggest a VOX switch with a push-to-talk option for determining speech from noise. In the present invention which is a voice detection means (algorithm) is streamlined and robustized by using inter aIia, a nonparametric test such as a Kolmogorov-Smirnov Test. Cantrell addresses the dominant harmonic by essentially using a phase locked loop approach to control a notched filter. While the present invention focuses on speech enhancement, by the use of adaptive filters, the present invention is able to work with a wider variety of modulated signals, as well as with several given signals at a time. Elliot relates to zonal quieting to control the phase of a propeller or fan and does not appear to relate to speech enhancement. Likewise, Hill is concerned with reducing noise in rotating equipment, such as, a fan, and does not appear to relate to speech enhancement as in the present invention. Zinser merely provides a variation on the LMS algorithm.
Thus, the prior art fails to provide a noise cancellation and speech enhancement system and apparatus as described in the present invention. More specifically, the prior art fails to provide a noise cancellation system including a spectral subtractor and a push-to-talk or VOX switch which enables a speech/noise determination by use of test statistics including, for example, sample zero crossings, changes in the number of tonals, energy and a nonparametric test such as a Kolmogorov-Smirnov Test. Further, utilizing a spectral algorithm with a LMS algorithm in a noise cancellation and speech enhancement system and apparatus, as in the present invention, has not been taught or suggested. Furthermore, a noise cancellation system wherein the spectral algorithm not only employs the above-described test statistics, but also includes a constraint function for minimizing residual musical noise, as well as a tracking device to identify tonal noise components and predict trajectories thereof, as in the present invention, has not been taught or suggested. Further, the in-ear and in headset (or handset, e.g., for telephones) devices of the present invention which utilize the previously mentioned features have not been heretofore taught or suggested.
While all of the above-described prior art systems relate to acoustic noise cancellation, they are limited by the lack of performance in severe noise environments; namely, they fail to perform in severe noise environments wherein the noise is highly impulsive or poorly defined.